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Computational studies on potential new anti-Covid-19 agents with a multi-target mode of action
A compound that could inhibit multiple targets associated with SARS-CoV-2 infection would prove to be a drug of choice against the virus. Human receptor-ACE2, receptor binding domain (RBD) of SARS-CoV-2 S-protein, Papain-like protein of SARS-CoV-2 (PLpro), reverse transcriptase of SARS-CoV-2 (RdRp)...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier B.V. on behalf of King Saud University.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9101701/ https://www.ncbi.nlm.nih.gov/pubmed/35582633 http://dx.doi.org/10.1016/j.jksus.2022.102086 |
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author | Mohapatra, Ranjan K. Azam, Mohammad Mohapatra, Pranab K. Sarangi, Ashish K. Abdalla, Mohnad Perekhoda, Lina Yadav, Oval Al-Resayes, Saud I. Jong-Doo, Kim Dhama, Kuldeep Ansari, Azaj Seidel, Veronique Verma, Sarika Raval, Mukesh K. |
author_facet | Mohapatra, Ranjan K. Azam, Mohammad Mohapatra, Pranab K. Sarangi, Ashish K. Abdalla, Mohnad Perekhoda, Lina Yadav, Oval Al-Resayes, Saud I. Jong-Doo, Kim Dhama, Kuldeep Ansari, Azaj Seidel, Veronique Verma, Sarika Raval, Mukesh K. |
author_sort | Mohapatra, Ranjan K. |
collection | PubMed |
description | A compound that could inhibit multiple targets associated with SARS-CoV-2 infection would prove to be a drug of choice against the virus. Human receptor-ACE2, receptor binding domain (RBD) of SARS-CoV-2 S-protein, Papain-like protein of SARS-CoV-2 (PLpro), reverse transcriptase of SARS-CoV-2 (RdRp) were chosen for in silico study. A set of previously synthesized compounds (1–5) were docked into the active sites of the targets. Based on the docking score, ligand efficiency, binding free energy, and dissociation constants for a definite conformational position of the ligand, inhibitory potentials of the compounds were measured. The stability of the protein–ligand (P-L) complex was validated in silico by using molecular dynamics simulations using the YASARA suit. Moreover, the pharmacokinetic properties, FMO and NBO analysis were performed for ranking the potentiality of the compounds as drug. The geometry optimizations and electronic structures were investigated using DFT. As per the study, compound-5 has the best binding affinity against all four targets. Moreover, compounds 1, 3 and 5 are less toxic and can be considered for oral consumption. |
format | Online Article Text |
id | pubmed-9101701 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Authors. Published by Elsevier B.V. on behalf of King Saud University. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91017012022-05-13 Computational studies on potential new anti-Covid-19 agents with a multi-target mode of action Mohapatra, Ranjan K. Azam, Mohammad Mohapatra, Pranab K. Sarangi, Ashish K. Abdalla, Mohnad Perekhoda, Lina Yadav, Oval Al-Resayes, Saud I. Jong-Doo, Kim Dhama, Kuldeep Ansari, Azaj Seidel, Veronique Verma, Sarika Raval, Mukesh K. J King Saud Univ Sci Original Article A compound that could inhibit multiple targets associated with SARS-CoV-2 infection would prove to be a drug of choice against the virus. Human receptor-ACE2, receptor binding domain (RBD) of SARS-CoV-2 S-protein, Papain-like protein of SARS-CoV-2 (PLpro), reverse transcriptase of SARS-CoV-2 (RdRp) were chosen for in silico study. A set of previously synthesized compounds (1–5) were docked into the active sites of the targets. Based on the docking score, ligand efficiency, binding free energy, and dissociation constants for a definite conformational position of the ligand, inhibitory potentials of the compounds were measured. The stability of the protein–ligand (P-L) complex was validated in silico by using molecular dynamics simulations using the YASARA suit. Moreover, the pharmacokinetic properties, FMO and NBO analysis were performed for ranking the potentiality of the compounds as drug. The geometry optimizations and electronic structures were investigated using DFT. As per the study, compound-5 has the best binding affinity against all four targets. Moreover, compounds 1, 3 and 5 are less toxic and can be considered for oral consumption. The Authors. Published by Elsevier B.V. on behalf of King Saud University. 2022-07 2022-05-13 /pmc/articles/PMC9101701/ /pubmed/35582633 http://dx.doi.org/10.1016/j.jksus.2022.102086 Text en © 2022 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Original Article Mohapatra, Ranjan K. Azam, Mohammad Mohapatra, Pranab K. Sarangi, Ashish K. Abdalla, Mohnad Perekhoda, Lina Yadav, Oval Al-Resayes, Saud I. Jong-Doo, Kim Dhama, Kuldeep Ansari, Azaj Seidel, Veronique Verma, Sarika Raval, Mukesh K. Computational studies on potential new anti-Covid-19 agents with a multi-target mode of action |
title | Computational studies on potential new anti-Covid-19 agents with a multi-target mode of action |
title_full | Computational studies on potential new anti-Covid-19 agents with a multi-target mode of action |
title_fullStr | Computational studies on potential new anti-Covid-19 agents with a multi-target mode of action |
title_full_unstemmed | Computational studies on potential new anti-Covid-19 agents with a multi-target mode of action |
title_short | Computational studies on potential new anti-Covid-19 agents with a multi-target mode of action |
title_sort | computational studies on potential new anti-covid-19 agents with a multi-target mode of action |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9101701/ https://www.ncbi.nlm.nih.gov/pubmed/35582633 http://dx.doi.org/10.1016/j.jksus.2022.102086 |
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